A bioinformatics analysis of potential cellular communication networks in non-alcoholic steatohepatitis and colorectal adenoma using scRNA-seq and bulk-seq
2023 Journal of Gastrointestinal Oncology. All rights reserved..
Background: Non-alcoholic fatty liver disease (NAFLD) is the global most common chronic liver disease. Non-alcoholic steatohepatitis (NASH), an inflammatory subtype of NAFLD, has been shown to significantly increase the risk of colorectal adenoma (CRA). Therefore, from the perspective of bioinformatics analysis, the potential mechanisms of NASH/NAFLD-CRA can be explored.
Methods: In this study, we screened the differentially expressed genes (DEGs) and core effect pathways between NASH and CRA by analyzing the single-cell data of CRA patients and the high-throughput sequencing data (GSE37364 and GSE89632) in the online database. We screened therapeutic targets and biomarkers through gene function classification, pathway enrichment analysis, and protein-protein interaction network analysis. In terms of single cell data, we screened the core effect pathway and specific signal pathway of cell communication through cell annotation and cell communication analyses. The purpose of the study was to find potential biomarkers, therapeutic targets, and related effect pathways of NASH-CRA.
Results: NASH-CRA comorbidities were concentrated in inflammatory regulation-related pathways, and the core genes of disease progression included IL1B, FOSL1, EGR1, MYC, PTGS2, and FOS. The results suggested the key pathway of NASH-CRA might be the WNT pathway. The main cell signal communication pathways included WNT2B - (FZD6 + LRP5) and WNT2B - (FZD6 + LRP6). The send-receive process occurred in embryonic stem cells.
Conclusions: The core genes of NASH-CRA (FOS, EGR1, MYC, PTGS2, FOSL1, and IL1B) may participate in inflammation and immune responses through up-regulation in the process of disease occurrence, interfering with the pathophysiological process of CRA and NASH. NASH-CRA produces cell signal communication in the WNT pathway sent by WNT2B and received by FZD6, LRP5, and LRP6 in embryonic stem cells. These findings may help formulate early diagnosis and treatment strategies for CRA in NAFLD/NASH patients, and further explore corresponding prognostic markers and potential approaches. The significance of scRNA-seq in exploring tumor heterogeneity lies in promoting our understanding of the expression program of tumor related genes in tumor development patterns. However, the biggest challenge is that this analysis may miss out on some biologically significant gene expression programs.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2023 |
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Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:14 |
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Enthalten in: |
Journal of gastrointestinal oncology - 14(2023), 4 vom: 31. Aug., Seite 1770-1787 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Mo, Jiahao [VerfasserIn] |
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Links: |
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Themen: |
Bioinformatics analysis |
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Anmerkungen: |
Date Revised 19.09.2023 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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doi: |
10.21037/jgo-23-502 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM362173044 |
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100 | 1 | |a Mo, Jiahao |e verfasserin |4 aut | |
245 | 1 | 2 | |a A bioinformatics analysis of potential cellular communication networks in non-alcoholic steatohepatitis and colorectal adenoma using scRNA-seq and bulk-seq |
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520 | |a 2023 Journal of Gastrointestinal Oncology. All rights reserved. | ||
520 | |a Background: Non-alcoholic fatty liver disease (NAFLD) is the global most common chronic liver disease. Non-alcoholic steatohepatitis (NASH), an inflammatory subtype of NAFLD, has been shown to significantly increase the risk of colorectal adenoma (CRA). Therefore, from the perspective of bioinformatics analysis, the potential mechanisms of NASH/NAFLD-CRA can be explored | ||
520 | |a Methods: In this study, we screened the differentially expressed genes (DEGs) and core effect pathways between NASH and CRA by analyzing the single-cell data of CRA patients and the high-throughput sequencing data (GSE37364 and GSE89632) in the online database. We screened therapeutic targets and biomarkers through gene function classification, pathway enrichment analysis, and protein-protein interaction network analysis. In terms of single cell data, we screened the core effect pathway and specific signal pathway of cell communication through cell annotation and cell communication analyses. The purpose of the study was to find potential biomarkers, therapeutic targets, and related effect pathways of NASH-CRA | ||
520 | |a Results: NASH-CRA comorbidities were concentrated in inflammatory regulation-related pathways, and the core genes of disease progression included IL1B, FOSL1, EGR1, MYC, PTGS2, and FOS. The results suggested the key pathway of NASH-CRA might be the WNT pathway. The main cell signal communication pathways included WNT2B - (FZD6 + LRP5) and WNT2B - (FZD6 + LRP6). The send-receive process occurred in embryonic stem cells | ||
520 | |a Conclusions: The core genes of NASH-CRA (FOS, EGR1, MYC, PTGS2, FOSL1, and IL1B) may participate in inflammation and immune responses through up-regulation in the process of disease occurrence, interfering with the pathophysiological process of CRA and NASH. NASH-CRA produces cell signal communication in the WNT pathway sent by WNT2B and received by FZD6, LRP5, and LRP6 in embryonic stem cells. These findings may help formulate early diagnosis and treatment strategies for CRA in NAFLD/NASH patients, and further explore corresponding prognostic markers and potential approaches. The significance of scRNA-seq in exploring tumor heterogeneity lies in promoting our understanding of the expression program of tumor related genes in tumor development patterns. However, the biggest challenge is that this analysis may miss out on some biologically significant gene expression programs | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Non-alcoholic steatohepatitis (NASH) | |
650 | 4 | |a bioinformatics analysis | |
650 | 4 | |a cellular communication networks | |
650 | 4 | |a colorectal adenoma (CRA) | |
650 | 4 | |a single-cell RNA sequencing (scRNA-seq) | |
700 | 1 | |a Liu, Chang |e verfasserin |4 aut | |
700 | 1 | |a Li, Zhuolin |e verfasserin |4 aut | |
700 | 1 | |a Fan, Longxiu |e verfasserin |4 aut | |
700 | 1 | |a Wu, Shaohua |e verfasserin |4 aut | |
700 | 1 | |a Husain, Hatim |e verfasserin |4 aut | |
700 | 1 | |a Zhong, Cailing |e verfasserin |4 aut | |
700 | 1 | |a Zhang, Beiping |e verfasserin |4 aut | |
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